Titlebook: Statistical Signal Processing; Frequency Estimation Debasis Kundu,Swagata Nandi Book 20121st edition The Author(s) 2012 Convergence.Informa

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Related Models,le non-linear parameter instead of ., in case of multiple sinusoidal model. Similarly, if the gap between two consecutive frequencies is approximately same, then the suitable model is the .. We call these models as “related models” of the sinusoidal frequency model.

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Asymptotic Properties,es deal with properties of estimators under the assumption that the sample size increases indefinitely. The statistical models, observed in signal processing literature, are mostly very complicated non-linear models. Even a single component sinusoidal component model is highly non-linear in its freq

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Estimating the Number of Components,pments, it has been assumed that the number of components ‘.’ is known in advance. But in practice estimation of . is also a very important problem. Although, during the last 35 to 40 years extensive work has been done in estimating the frequencies of model (3.1), not that much of attention has been

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Multidimensional Models,frequency models and discuss several issues related to them. The 2-D and 3-D sinusoidal frequency models are natural generalizations of 1-D sinusoidal frequency model (3.1), and these models have various applications.

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Introduction,Signal processing may broadly be considered to involve the recovery of information from physical observations. The received signal is usually disturbed by thermal, electrical, atmospheric, or intentional interferences. Due to random nature of the signal, statistical techniques play important roles in analyzing the signal.

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Estimation of Frequencies,In this section, we provide different estimation procedures of the frequencies of a periodic signal.